Borrowing it
Nothing to install: this file belongs to tusharagg1/aifolimizer. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/tusharagg1/aifolimizer/master/.claude/skills/pre-trade-check/SKILL.mdgit clone --depth 1 https://github.com/tusharagg1/aifolimizerWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tusharagg1/aifolimizer/pre-trade-check)<a href="https://agentmods.dev/skills/tusharagg1/aifolimizer/pre-trade-check"><img src="https://agentmods.dev/badge/skills/tusharagg1/aifolimizer/pre-trade-check/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tusharagg1/aifolimizer/pre-trade-check"><img src="https://agentmods.dev/badge/skills/tusharagg1/aifolimizer/pre-trade-check.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00094 | $0.02729 |
| Opus 5 | $0.00047 | $0.01365 |
| Sonnet 5 | $0.00019 | $0.00546 |
| Haiku 4.5 | $0.00009 | $0.00273 |
Grade A, and why
pre-trade-check scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 10d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 158 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Pre-Trade Check (Behavioral Guardrail)
Goal
Stop bad trades before they happen. This skill is a filter, not a recommender. Output is PASS or REJECT with reasons. Most retail losses come from emotional entries - this skill makes those entries explicit and refusable.
When to invoke
Any time the user is considering a buy or sell. Especially:
- Symbol seen on TikTok / X / Reddit / news
- "Friend told me about X"
- After a big up day on a name
- After a big down day on a held name (panic-sell candidate)
- Any FOMO / regret language
How to run
Step 0 - Establish intent (REQUIRED before any tool call):
If user has not stated, ask explicitly:
- Ticker?
- Direction? (BUY new / ADD existing / SELL / TRIM)
- Horizon? (intraday / swing days-to-weeks / position 1-6mo / long-term)
- Dollar amount considered?
- Why now? (specific catalyst, technical setup, or "saw it on X")
If user can't answer #5 with a specific reason that isn't "saw it on social media" → output REJECT: no thesis and stop. Do not run other tools.
Step 1 - Pull state (parallel):
mcp__aifolimizer__get_profile- total capital, per-account cashmcp__aifolimizer__get_portfolio- current holdings, weights, existing position in this ticker if anymcp__aifolimizer__get_technicalswithsymbols=[TICKER]mcp__aifolimizer__get_fundamentalswithsymbols=[TICKER]mcp__aifolimizer__get_positioning_signalswithsymbols=[TICKER]mcp__aifolimizer__get_news_headlineswithsymbols=[TICKER],limit=10mcp__aifolimizer__get_live_track_record(no args) - user's own win-rate over last 30dmcp__aifolimizer__get_ticker_decision_historywithticker=TICKER- prior decisions on this namemcp__aifolimizer__get_personal_context(no args) - usederived.province+derived.marginal_tax_rate_pctto ground the non-reg short-term-gain warning in Rules. Ifpresent == false, state that warning as generic (no rate).
Step 2 - Run filter gates (in order, stop at first REJECT for fatal gates):
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 10d ago First seen · 158 lines · 94 tokens per session scan A 560ca1c2df91
pre-trade-check is a skill published in the GitHub repository tusharagg1/aifolimizer (2 stars, last pushed 8d ago), licensed MIT. It adds 94 tokens to every session and 2,729 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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